Analog VLSI Implementation of Neural Systems (The Springer International Series in Engineering and Computer Science)

ISBN 10: 0792390407 / ISBN 13: 9780792390404

Published by Springer, 1989

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Seller Inventory # ERICA77307923904076

Bibliographic Details

• Title: Analog VLSI Implementation of Neural Systems (The Springer International Series in Engineering and Computer Science)
• Publisher: Springer
• Publication Date: 1989
• Language: English
• ISBN 10: 0792390407
• ISBN 13: 9780792390404
• Binding: Hardcover
• Condition: Like New
• Book Type: book

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Synopsis

This volume contains the proceedings of a workshop on Analog Integrated Neural Systems held May 8, 1989, in connection with the International Symposium on Circuits and Systems. The presentations were chosen to encompass the entire range of topics currently under study in this exciting new discipline. Stringent acceptance requirements were placed on contributions: (1) each description was required to include detailed characterization of a working chip, and (2) each design was not to have been published previously. In several cases, the status of the project was not known until a few weeks before the meeting date. As a result, some of the most recent innovative work in the field was presented. Because this discipline is evolving rapidly, each project is very much a work in progress. Authors were asked to devote considerable attention to the shortcomings of their designs, as well as to the notable successes they achieved. In this way, other workers can now avoid stumbling into the same traps, and evolution can proceed more rapidly (and less painfully). The chapters in this volume are presented in the same order as the corresponding presentations at the workshop. The first two chapters are concerned with fmding solutions to complex optimization problems under a predefmed set of constraints. The first chapter reports what is, to the best of our knowledge, the first neural-chip design. In each case, the physics of the underlying electronic medium is used to represent a cost function in a natural way, using only nearest-neighbor connectivity.